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Reservoir (Updates) - FortunaFi

Prepared by:

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HALBORN

Last Updated Unknown date

Date of Engagement: September 20th, 2024 - September 26th, 2024

Summary

100% of all REPORTED Findings have been addressed

All findings

2

Critical

0

High

0

Medium

0

Low

1

Informational

1

Table of Contents

1. Introduction

FortunaFi engaged Halborn to conduct a security assessment on smart contracts beginning on 09/20/2024 and ending on 09/26/2024. The security assessment was scoped to the smart contracts provided to the Halborn team.

2. Assessment Summary

The team at Halborn dedicated 1 week for the engagement and assigned one full-time security engineer to evaluate the security of the smart contract.

The security engineer is a blockchain and smart-contract security expert with advanced penetration testing, smart-contract hacking, and deep knowledge of multiple blockchain protocols

The purpose of this assessment is to:

    • Ensure that smart contract functions operate as intended.

    • Identify potential security issues with the smart contracts.

In summary, Halborn identified some improvements to reduce the likelihood and impact of risks, which were successfully addressed by the FortunaFi team. The main ones were the following:

    • Unsafe typecasting of integers in oracle price retrieval functions, which could lead to silent overflows or underflows.

    • Unintended burning of excess stablecoins in the redeem function, preventing recovery of accidentally sent tokens.

    • Lack of input validation and zero-address checks in critical functions and the constructor.

3. Test Approach and Methodology

Halborn performed a combination of manual, semi-automated and automated security testing to balance efficiency, timeliness, practicality, and accuracy regarding the scope of this assessment. While manual testing is recommended to uncover flaws in logic, process, and implementation; automated testing techniques help enhance coverage of the code and can quickly identify items that do not follow security best practices. The following phases and associated tools were used throughout the term of the assessment:

    • Research into architecture and purpose.

    • Smart contract manual code review and walk-through.

    • Manual assessment of use and safety for the critical Solidity variables and functions in scope to identify any vulnerability classes

    • Manual testing by custom scripts.

    • Static Analysis of security for scoped contract, and imported functions. (Slither)

    • Local deployment and testing ( Foundry)

4. RISK METHODOLOGY

Every vulnerability and issue observed by Halborn is ranked based on two sets of Metrics and a Severity Coefficient. This system is inspired by the industry standard Common Vulnerability Scoring System.
The two Metric sets are: Exploitability and Impact. Exploitability captures the ease and technical means by which vulnerabilities can be exploited and Impact describes the consequences of a successful exploit.
The Severity Coefficients is designed to further refine the accuracy of the ranking with two factors: Reversibility and Scope. These capture the impact of the vulnerability on the environment as well as the number of users and smart contracts affected.
The final score is a value between 0-10 rounded up to 1 decimal place and 10 corresponding to the highest security risk. This provides an objective and accurate rating of the severity of security vulnerabilities in smart contracts.
The system is designed to assist in identifying and prioritizing vulnerabilities based on their level of risk to address the most critical issues in a timely manner.

4.1 EXPLOITABILITY

Attack Origin (AO):
Captures whether the attack requires compromising a specific account.
Attack Cost (AC):
Captures the cost of exploiting the vulnerability incurred by the attacker relative to sending a single transaction on the relevant blockchain. Includes but is not limited to financial and computational cost.
Attack Complexity (AX):
Describes the conditions beyond the attacker’s control that must exist in order to exploit the vulnerability. Includes but is not limited to macro situation, available third-party liquidity and regulatory challenges.
Metrics:
EXPLOITABILITY METRIC (mem_e)METRIC VALUENUMERICAL VALUE
Attack Origin (AO)Arbitrary (AO:A)
Specific (AO:S)		1
0.2
Attack Cost (AC)Low (AC:L)
Medium (AC:M)
High (AC:H)		1
0.67
0.33
Attack Complexity (AX)Low (AX:L)
Medium (AX:M)
High (AX:H)		1
0.67
0.33
Exploitability EE is calculated using the following formula:

E=∏meE = \prod m_e

4.2 IMPACT

Confidentiality (C):
Measures the impact to the confidentiality of the information resources managed by the contract due to a successfully exploited vulnerability. Confidentiality refers to limiting access to authorized users only.
Integrity (I):
Measures the impact to integrity of a successfully exploited vulnerability. Integrity refers to the trustworthiness and veracity of data stored and/or processed on-chain. Integrity impact directly affecting Deposit or Yield records is excluded.
Availability (A):
Measures the impact to the availability of the impacted component resulting from a successfully exploited vulnerability. This metric refers to smart contract features and functionality, not state. Availability impact directly affecting Deposit or Yield is excluded.
Deposit (D):
Measures the impact to the deposits made to the contract by either users or owners.
Yield (Y):
Measures the impact to the yield generated by the contract for either users or owners.
Metrics:
IMPACT METRIC (mIm_I)METRIC VALUENUMERICAL VALUE
Confidentiality (C)None (C:N)
Low (C:L)
Medium (C:M)
High (C:H)
Critical (C:C)		0
0.25
0.5
0.75
1
Integrity (I)None (I:N)
Low (I:L)
Medium (I:M)
High (I:H)
Critical (I:C)		0
0.25
0.5
0.75
1
Availability (A)None (A:N)
Low (A:L)
Medium (A:M)
High (A:H)
Critical (A:C)		0
0.25
0.5
0.75
1
Deposit (D)None (D:N)
Low (D:L)
Medium (D:M)
High (D:H)
Critical (D:C)		0
0.25
0.5
0.75
1
Yield (Y)None (Y:N)
Low (Y:L)
Medium (Y:M)
High (Y:H)
Critical (Y:C)		0
0.25
0.5
0.75
1
Impact II is calculated using the following formula:

I=max(mI)+∑mI−max(mI)4I = max(m_I) + \frac{\sum{m_I} - max(m_I)}{4}

4.3 SEVERITY COEFFICIENT

Reversibility (R):
Describes the share of the exploited vulnerability effects that can be reversed. For upgradeable contracts, assume the contract private key is available.
Scope (S):
Captures whether a vulnerability in one vulnerable contract impacts resources in other contracts.
Metrics:
SEVERITY COEFFICIENT (CC)COEFFICIENT VALUENUMERICAL VALUE
Reversibility (rr)None (R:N)
Partial (R:P)
Full (R:F)		1
0.5
0.25
Scope (ss)Changed (S:C)
Unchanged (S:U)		1.25
1
Severity Coefficient CC is obtained by the following product:

C=rsC = rs

The Vulnerability Severity Score SS is obtained by:

S=min(10,EIC∗10)S = min(10, EIC * 10)

The score is rounded up to 1 decimal places.
SeverityScore Value Range
Critical9 - 10
High7 - 8.9
Medium4.5 - 6.9
Low2 - 4.4
Informational0 - 1.9

5. SCOPE

REPOSITORY
(a) Repository: reservoir
(b) Assessed Commit ID: 2a49b0a
(c) Items in scope:
  • src/adapters/VaultSharesOracleV2.sol
  • src/adapters/MorphoRUSDAdapter.sol
  • src/LiquidTerm.sol
↓ Expand ↓
Out-of-Scope: New features/implementations after the remediation commit IDs.

6. Assessment Summary & Findings Overview

Critical

0

High

0

Medium

0

Low

1

Informational

1

Security analysisRisk levelRemediation Date
Unintended Burning of Excess Stablecoins in Redeem FunctionLowSolved - 09/30/2024
Unsafe Type Casting in Oracle Price Retrieval FunctionsInformationalSolved - 09/30/2024

7. Findings & Tech Details

7.1 Unintended Burning of Excess Stablecoins in Redeem Function

//

Low

Description
BVSS
Recommendation
Remediation Comment

7.2 Unsafe Type Casting in Oracle Price Retrieval Functions

//

Informational

Description
BVSS
Recommendation
Remediation Comment

8. Automated Testing

Halborn strongly recommends conducting a follow-up assessment of the project either within six months or immediately following any material changes to the codebase, whichever comes first. This approach is crucial for maintaining the project’s integrity and addressing potential vulnerabilities introduced by code modifications.

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Reservoir (Updates)

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